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Significance of E. Coli Evolution Experiments (view source)
Revision as of 13:56, March 14, 2009
, 13:56, March 14, 2009Some reorganization and added experiment 3
Blount, Borland, and [[Lenski]]<ref> http://www.pnas.org/content/105/23/7899.full.pdf</ref> claimed that a key evolutionary innovation was observed during a [[laboratory]] [[experiment]]. That claim is false. The claim was based on incorrect measurements of statistical significance. Rather than using a test from the statistics literature, a flawed test was contrived and used to measure significance. The flawed test (“mean mutation generation”) produced artificially low p-values.
Blount, Borland, and [[Lenski]]<ref> http://www.pnas.org/content/105/23/7899.full.pdf</ref> claimed that a key evolutionary innovation was observed during a [[laboratory]] [[experiment]]. That claim is false. The claim was based on incorrect measurements of statistical significance. Rather than using a test from the statistics literature, a flawed test was contrived and used to measure significance. The flawed test (“mean mutation generation”) produced artificially low p-values.
==Experiment One Data==
The data from experiment one of the paper is shown below (see Table 1 of the paper). The expected outcomes under the null hypothesis (no evolutionary innovation occurs) are also shown.
The data from experiment one of the paper is shown below (see Table 1 of the paper). The expected outcomes under the null hypothesis (no evolutionary innovation occurs) are also shown.
When the flawed test is used to compute the significance of this data, the p-value is 0.0085 (see Table 2 of the paper). This p-value is considered statistically significant. However, when the data is analyzed using a standard method (the chi-square test) the p-value is 0.19. This p-value is much larger than the one from the paper and indicates that there is no reason to reject the null hypothesis. The chi-square test p-value for experiment two is small (0.0004). However, experiment three is not statistically significant because its p-value is 0.22.
When the flawed test is used to compute the significance of this data, the p-value is 0.0085 (see Table 2 of the paper). This p-value is considered statistically significant. However, when the data is analyzed using a standard method (the chi-square test) the p-value is 0.19. This p-value is much larger than the one from the paper and indicates that there is no reason to reject the null hypothesis. The chi-square test p-value for experiment two is small (0.0004). However, experiment three is not statistically significant because its p-value is 0.22.
The chi-square test is a common statistical method.<ref>''Mathematical Statistics with Applications'' by Wackerly, Mendenhall, and Scheaffer, Section 14.4.</ref> It can be implemented in Microsoft Excel. If the numbers from the last four columns of the table above (excluding the “totals” row) are entered into Excel in rows 1-12 and columns A-D, then the p-value can be computed by entering “=CHITEST(A1:B12,C1:D12)” into any empty cell of the spreadsheet.
The chi-square test is a common statistical method.<ref>''Mathematical Statistics with Applications'' by Wackerly, Mendenhall, and Scheaffer, Section 14.4.</ref> It can be implemented in Microsoft Excel. If the numbers from the last four columns of the experiment one data table (excluding the “totals” row) are entered into Excel in rows 1-12 and columns A-D, then the p-value can be computed by entering “=CHITEST(A1:B12,C1:D12)” into any empty cell of the spreadsheet.
==Experiment Three Data==
The experiment three data from Blount et al. is shown in the table below. The expected numbers of mutants under the null hypothesis (constant mutation rate) is also shown.
{|class="wikitable" style="text-align:center"
|-
!Generation
!Trials
!Mutants
!Statics
!Expected Mutants
!Expected Statics
|-
|0
|200
|0
|200
|0.571
|199.429
|-
|10000
|200
|0
|200
|0.571
|199.429
|-
|20000
|200
|0
|200
|0.571
|199.429
|-
|25000
|200
|0
|200
|0.571
|199.429
|-
|27500
|200
|2
|198
|0.571
|199.429
|-
|29000
|200
|0
|200
|0.571
|199.429
|-
|30000
|200
|2
|198
|0.571
|199.429
|-
|30500
|200
|0
|200
|0.571
|199.429
|-
|31000
|200
|0
|200
|0.571
|199.429
|-
|31500
|200
|0
|200
|0.571
|199.429
|-
|32000
|200
|1
|199
|0.571
|199.429
|-
|32500
|200
|1
|199
|0.571
|199.429
|-
|-
!Total
!2800
!8
!2792
!8
!2792
|}
==Comparison of p-Values==
==Comparison of p-Values==
==See Also==
==See Also==
http://www.sciencenews.org/index/feature/activity/view/id/40006/title/Molecular_Evolution
http://www.sciencenews.org/index/feature/activity/view/id/40006/title/Molecular_Evolution
http://sciencenews.org/view/generic/id/40649/title/FOR_KIDS_Hitting_the_redo_button_on_evolution
http://sciencenews.org/view/generic/id/40649/title/FOR_KIDS_Hitting_the_redo_button_on_evolution